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"Protein Side-chain Packing" has an ever-increasing application in the field of bio-informatics, dating from the early methods of homology modeling to protein design and to the protein docking. However, this problem is computationally known to be NP-hard. In this regard, we have developed a novel approach to solve this problem using the notion of a maximum(More)
MOTIVATION Accurate computational prediction of protein functional sites is critical to maximizing the utility of recent high-throughput sequencing efforts. Among the available approaches, position-specific conservation scores remain among the most popular due to their accuracy and ease of computation. Unfortunately, high false positive rates remain a(More)
With the advent of experimental technologies like chemical cross-linking, it has become possible to obtain distances between specific residues of a newly sequenced protein. These types of experiments usually are less time consuming than X-ray crystallography or NMR. Consequently, it is highly desired to develop a method that incorporates this distance(More)
In nonlinear and chaotic time series prediction, constructing the mathematical model of the system dynamics is not an easy task. Partially connected Artificial Neural Network with Evolvable Topology (PANNET) is a new paradigm for prediction of chaotic time series without access to the dynamics and essential memory depth of the system. Evolvable topology of(More)
Protein threading with profiles in which constraints on distances between residues are given is known to be NP-hard. Moreover, a simple algorithm known as CLIQUETHREAD based on efficient reduction to maximum edge-weight clique finding problem has been known to be a practical algorithm for solving the protein threading problem with profiles and constraints.(More)
SUMMARY The protein threading problem with profiles is known to be efficiently solvable using dynamic programming. In this paper, we consider a variant of the protein threading problem with profiles in which constraints on distances between residues are given. We prove that protein threading with profiles and constraints is NP-hard. Moreover , we show a(More)
Prediction of protein functional sites from sequence-derived data remains an open bioinformatics problem. We have developed a phylogenetic motif (PM) functional site prediction approach that identifies functional sites from alignment fragments that parallel the evolutionary patterns of the family. In our approach, PMs are identified by comparing tree(More)
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